Two things are already clear. The race for AI is heating up. And even before a winner emerges, the contest is changing the way that big tech deploys the technology
to assess the creditworthiness of loan applicants. Apple’s acquisitions have historically been small, notes Wasmi Mohan of Bank of America. But they tend to be quickly folded into existing products.hiring, too, is ramping up. A greater share of jobs listed by Google, Meta and Microsoft requireexpertise than they did, on average, over the past three years . Data from PredictLeads suggest that since 2019 nearly one in four of Alphabets’s job listings have been-related . Meta came second, at 8%.
Meta, in particular, is gaining a reputation for being less tight-lipped about its work than its fellow tech giants. Meta’s-software library, called PyTorch, has been available to anyone for a while; since February academic researchers can freely use its large language model called, and details of its training and biases have also been made public. All this, says Joelle Pinneau, the head of Meta’s open-research programme, helps it attract the brightest minds .
Indeed, if you adjust Meta’s research output for its revenues and headcount, which are much smaller than Alphabet’s or Microsoft’s, and only consider the most-cited papers, Mr Zuckerberg’s firm tops the research league table. And, points out Ajay Agrawal of the University of Toronto, openness brings two added benefits besides luring the best brains. Low-costcan make it cheaper for creators to make content, including texts and videos, that draw more eyeballs to Meta’s social networks.
If the platform-shift thesis is correct, big tech could yet be upset by newcomers, rather as they themselves upset an earlier generation of technology giants. The mass of resources that big tech is ploughing into the technology reflects a desire to remain not just relevant, but dominant. Whether or not they succeed, one thing is certain: these are just the modest beginnings of the
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